#!/usr/bin/python3
# coding=utf-8

# Copyright (c) 2024 Huawei Technologies Co., Ltd.
# This file is a part of the CANN Open Software.
# Licensed under CANN Open Software License Agreement Version 1.0 (the "License").
# Please refer to the License for details. You may not use this file except in compliance with the License.
# THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
# INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
# See LICENSE in the root of the software repository for the full text of the License.
# ======================================================================================================================

import os

import numpy as np


def gen_golden_data():
    src_type = np.float16
    dst_type = np.float32

    m, n, k, is_bias, is_atrans, is_btrans = 128, 2048, 1024, False, True, False

    x1_gm = np.random.randint(-10, 10, [m, k]).astype(src_type)
    x2_gm = np.random.randint(-10, 10, [k, n]).astype(src_type)
    bias_gm = np.random.randint(-10, 10, [n, ]).astype(dst_type)

    if is_bias:
        golden = np.matmul(x1_gm.astype(dst_type), x2_gm.astype(dst_type)).astype(dst_type) + bias_gm
    else:
        golden = np.matmul(x1_gm.astype(dst_type), x2_gm.astype(dst_type)).astype(dst_type)

    if not os.path.exists("input"):
        os.makedirs("input")
    if not os.path.exists("output"):
        os.makedirs("output")

    if is_atrans:
        x1_gm = x1_gm.transpose()
    if is_btrans:
        x2_gm = x2_gm.transpose()

    x1_gm.tofile("./input/x1_gm.bin")
    x2_gm.tofile("./input/x2_gm.bin")
    bias_gm.tofile("./input/bias_gm.bin")
    golden.tofile("./output/golden.bin")


if __name__ == "__main__":
    gen_golden_data()
